The Case for Deterministic AI Agent Policies
AI agents decide probabilistically, but safety constraints shouldn't. Why deterministic policy enforcement outside the model produces more reliable agent systems.
MCP Security: Why Prompt Guardrails Aren't Enough
Prompt guardrails for MCP agents are bypassable and unauditable. Why deterministic policy enforcement at the transport layer is the real security primitive.
What Happens When Your AI Agent Goes Rogue
What happens when your AI agent goes rogue? Six failure modes — runaway loops, spending spirals, destructive ops — and the deterministic policies that stop them.
Rate Limiting MCP Tool Calls: A Practical Guide
Learn how to add per-tool and global rate limits to MCP agents with YAML policies. Covers counters, wildcards, and stateful tracking.
How to Add Spending Controls to Any MCP Agent
A step-by-step guide to adding transaction limits, daily spend caps, and currency restrictions to MCP-connected AI agents using YAML policies and the Intercept proxy.
One Command to Policy-Enforced Agents: Introducing the CLI Init Tool and MCP Server
npx @policylayer/mcp init takes you from zero to policy-enforced AI agent in under a minute. Browser auth, guided setup, and MCP tools your agent discovers automatically.
How to Add Spending Controls to Any MCP Agent
MCP servers are giving AI agents access to wallets, bridges, and DeFi. Here's how to enforce spending limits on any MCP-powered agent in under five minutes.